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Wireless sensor network (WSN) is an emerging technology used in emergency scenarios. There are a number of possible threats to WSNs because they use unsupervised IP addresses. Securing networks with unattended sensors is a real challenge nowadays. Sensor nodes lack power and storage, making them incompatible with normal security checks. It will be vital to make advancements in sensor network architecture and protocol design. There will be more vulnerability to attack if there is a lack of security. Especially, one key attack is node replication which induces the sensor node to acts as an original node, collecting data from the network and sending it to the attacker. In dynamic WSN, detecting an assault is difficult to find replica nodes. Therefore, this paper proposes a Strategic Security System (SSS) to discover replica nodes in static and dynamic distributed WSNs. It is mainly focused on enhancing detection accuracy, time delay, and communication overhead. The present system includes Single Stage Memory Random Walk with Network Division (SSRWND) and a Random-walk-based approach to detect clone attacks (RAWL). The proposed system has less memory and better detection accuracy.

SummaryWireless sensor network (WSN) is an environmental monitoring system exposing sensor nodes to various attacks. Jamming is an attack that disrupts the entire sensor network and affects the network's life span. The jammer broadcasts the signal at a frequency similar to the broadcast signal to jam the corresponding sensor node. There are many jamming detection schemes that only detect the jamming node, but they do not focus on eliminating the node that is not jamming. In this article, a novel strategy is used along with optimization to eliminate the disturbance in the sensor network and save the power consumed by nodes. The system uses the edge node, the sub‐edge node, and the cluster head for detection of jamming attack. Hyperbolic optimization is implemented in the cluster to eliminate data transmission failures. The proposed model considers the node's round trip time to detect jamming attacks. The optimization method considers the cluster head as the cluster member based on the probability of jamming in the network. The design is implemented and analyzed in MATLAB platform. As a result, the proposed method has improved the detection accuracy to 11.1% compared with extant techniques.

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